Effects of DNA methylation on cardiometabolic risk factors: a systematic review and meta-analysis

Background Epigenetic changes, especially DNA methylation have a main role in regulating cardiometabolic disorders and their risk factors. This study provides a review of the current evidence on the association between methylation of some genes (LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3, and LEP) and cardiometabolic risk factors. Methods A systematic literature search was conducted in electronic databases including Web of Science, PubMed, EMBASE, Google Scholar and Scopus up to end of 2020. All observational human studies (cross-sectional, case–control, and cohort) were included. Studies that assessed the effect of DNA methylation on cardiometabolic risk factors were selected. Results Among 1398 articles, eight studies and twenty-one studies were included in the meta-analysis and the systematic review, respectively. Our study showed ABCG1 and LINE1 methylation were positively associated with blood pressure (Fisher’s zr = 0.07 (0.06, 0.09), 95% CI: 0.05 to 0.08). Methylation in LINE1, ABCG1, SREBF1, PHOSPHO1 and ADRB3 had no significant association with HDL levels (Fisher’s zr = − 0.05 (− 0.13, 0.03), 95% CI:-0.12 to 0.02). Positive association was existed between LINE1, ABCG1 and LEP methylation and LDL levels (Fisher’s zr = 0.13 (0.04, 0.23), 95% CI: 0.03 to 0.23). Moreover, positive association was found between HbA1C and ABCG1 methylation (Fisher’s zr = 0.11 (0.09, 0.13), 95% CI: 0.09 to 0.12). DNA methylation of LINE1, ABCG1 and SREBF1 genes had no significant association with glucose levels (Fisher’s zr = 0.01 (− 0.12, 0.14), 95% CI:-0.12 to 0.14). Conclusion This meta-analysis showed that DNA methylation was associated with some cardiometabolic risk factors including LDL-C, HbA1C, and blood pressure. Registration Registration ID of the protocol on PROSPERO is CRD42020207677.

is the main epigenetic modifications without any changes in the DNA sequence. DNA methylation has a key role in the development of cardiometabolic disorders and their risk factors [6]. Several studies have assessed the relationship between DNA methylation at different loci of different genes with cardiometabolic risk factors. However, there are inconsistent findings [7][8][9][10]. Some results did not show any significant association between DNA methylation and cardiometabolic risk factors [9,11], whereas some of them confirmed these associations [12][13][14][15][16].
Study on epigenetic changes and their association with cardio-metabolic disorders can be a valuable way for prevention and treatment of NCDs [5,17]. Several epigenetic changes might affect cardiometabolic risk factors. Some genes, including Long interspersed nuclear element-1 (LINE1), ATP-binding cassette sub-family G member 1 (ABCG1), Sterol regulatory element-binding transcription factor 1 (SREBF1), Phosphatase orphan 1 (PHOSPHO1), Adrenoceptor Beta 3 (ADRB3) and Leptin (LEP) have been assessed more than others. This study aims to provide a summary of the literature that evaluated the relationship between methylation of different cytosine-phosphate-guanine (CpG) sites of LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3 and LEP genes and cardiometabolic risk factors including high-density lipoprotein cholesterol (HDL), low-density lipoprotein cholesterol (LDL), Hemoglobin A1C (HbA1C), blood glucose and blood pressure (BP).

Search strategy and study selection
The present study was conducted according to the guideline of Preferred Reporting Items for Systematic Reviews and Meta-Analyses, PRISMA [18]. The protocol was registered on PROSPERO (ID: CRD42020207677). A systematic literature search was conducted in Web of Science, Medical databases (PubMed), EMBASE, Google Scholar and Scopus, up to end of 2020. The following search terms were used: ("Epigenetic OR "Epigenomic" OR "methylation" OR "acetylation") AND ("Metabolic syndrome" OR "MetS" OR "insulin resistance syndrome" OR "cardiometabolic" OR "cardiometabolic risk factor"). We assessed the list of review articles references to find undetected relevant studies. Two researchers screened the records independently and selected relevant studies. In cases of nonconformity, the senior researchers were consulted. Titles and abstracts of the records were checked based on the inclusion and exclusion criteria.

Inclusion and exclusion criteria
Studies with the following criteria were included: 1. All observational studies (cross-sectional, case-control, and cohort) on adult individuals; 2. English language studies; 3. Studies that assessed the effect of epigenetic changes on cardiometabolic risk factors including HDL, LDL, Total cholesterol, glucose (FBS (fasting blood sugar) and random glucose levels), insulin levels, homeostatic model assessment for insulin resistance (HOMA-IR) and Hb1AC, without restriction of gender, race, ethnicity and year of publication; 4. Studies with available and extractable data; 5.Studies that extracted DNA from blood or tissue.
Papers with the following criteria were excluded: 1. Animal studies 2. Duplicate publications; 3. RNA epigenetic changes.

Data extraction
After screening studies, the number of articles on some genes including LINE-1, ABCG1, PHOSPHO1, SREBF1, LPL and ADRB3 were more than others; therefore, metaanalyses were particularly conducted on these six genes. The following information was extracted from eligible studies: bibliographic details (first author, publication year, and study design), sample size, participant's characteristics (gender, age, and body mass index), type of tissue sample, covariate variables, genes and loci, and genes methylation associated with HDL, LDL, glucose, blood pressure, and Hb1AC.

Quality assessment
We assessed the quality of studies using the Strengthening the Reporting of Observational studies in Epidemiology guidelines (STROBE) checklist [19,20]. This checklist consists of 22 items with different sections including title and abstract (1 item), introduction (2 items), methods (9 items), results (5 items), sections (4 items), and other information (1 item). Range of score is between zero and twenty-two. Two reviewers assessed the quality of articles independently, and in case of disagreement between the assigned scores, consulted with the third reviewer.

Statistical analysis
The Correlation coefficient of selected studies was applied for pooled analysis. The potential heterogeneity across studies was evaluated using the Cochran's Q-test and expressed using the I 2 index. The pooled results were calculated by the random-effects model. Subgroup analyses based on CpG sites were performed to seek the sources of heterogeneity. In addition, meta-regression was used for assessing the mean age, mean BMI, sample size, and the year of publication of studies as the possible source of heterogeneity. The sensitivity of analysis was performed by excluding one study at a time to gauge the robustness of our results. Publication bias was evaluated by Funnel plot and Egger's test. The possible publication's bias was adjusted using the trim and fill method. All statistical analyses were conducted using the STATA 12.0 software (STATA Corp, College Station, Texas, USA). The significance level was set at p < 0.05.

Association between DNA methylation and HDL levels
Results of meta-analysis on studies indicated that the DNA methylation had inverse association with serum HDL levels (Fisher's z r = − 0.048 (95% CI:-0.126 to 0.029)) using the random effects model (Fig. 2). However, the results were not significant. Test for heterogeneity (Q = 669.527, P < 0.0001) suggested the heterogeneity among the true effects was significant. Funnel plot did not show asymmetry (Z = -0.256, p = 0.79).

Association between DNA methylation and LDL levels
Results of meta-analysis on studies indicated that the DNA methylation had positive association with serum LDL levels (Fisher's z r = 0.134 (95% CI: 0.035 to 0.233)) using the random effects model (Fig. 3). Test for heterogeneity (Q = 208.05, P < 0.0001) suggested the heterogeneity among the true effects was significant. Funnel plot did not show asymmetry (Z = 1.04, p = 0.29).

Association between DNA methylation and HbA1C
Results of meta-analysis on two studies indicated that the DNA methylation had positive association with HbA1C (Fisher's z r = 0.1110 (95% CI: 0.094 to 0.127)) using the   (Fig. 4). Test for heterogeneity (Q = 0.232, P = 0.62) suggested the heterogeneity among the true effects was not significant. However, the number of total valid studies was two and there was very low sample size for meta-analysis. Confidence intervals for heterogeneity parameters were very wide.

Association between DNA methylation and blood glucose
Results of meta-analysis on studies indicated that the DNA methylation had positive association with blood glucose levels (Fisher's z r = 0.011 (95% CI:-0.121 to 0.144)) using the random-effects model (Fig. 5). However, the results were not significant. Test for heterogeneity (Q = 104.3606, P < 0.0001) suggested the heterogeneity among the true effects was significant. Funnel plot shows asymmetry (Z = -2.670, p = 0.007). Based on the regression test for funnel plot asymmetry, there was a significant publication bias among the results. So, we need to add two studies with positive correlation coefficient.

Association between DNA methylation and blood pressure
The findings of this meta-analysis on studies showed that DNA methylation had significant positive association with BP (Fisher's z r = 0.073 (95% CI: 0.056 to 0.089)) using random effects model (Fig. 6). Test for heterogeneity (Q = 8.087, P = 0.77) suggested the heterogeneity among the true effects was negligible. Funnel plot did not show asymmetry (Z = -1.141, p = 0.25).
The main reason of heterogeneity in our study was the difference in the gene sequences and sites of methylation in researches. Study participant characteristics such as age, gender and medical history, differences in study design and variation in results were reasons of heterogeneity.

Discussion
The current systematic review and meta-analysis showed the association between DNA methylation of LINE1, ABCG1, PHOSPHO1, SREBF1, LPL, ADRB3 genes and cardiometabolic risk factors, including HDL, LDL, blood glucose, blood pressure, and HbA1C.

DNA methylation and levels of HDL and LDL
Our findings did not show any significant association between DNA methylation of LINE1, ABCG1, SREBF1, PHOSPHO1 and ADRB3 genes and HDL levels. However, we found a positive association between DNA methylation of LINE1, ABCG1 and LEP genes and LDL levels. The majority of the included studies confirmed the association between DNA methylation of the mentioned genes and the lipid profile [12,15,16,24,25].
The prospective nested case-control study, with 15,353 Indian Asian participants, suggested DNA methylation of PHOSPHO1 and ABCG1 genes were significantly associated with HDL and LDL levels. Also, they showed that the SREBF1 methylation was associated with LDL levels [16]. A study on 228 individuals, aged 49-51 years, showed DNA methylation of the LINE-1 gene was positively associated with total cholesterol, triglycerides, and LDL and negatively associated with HDL and HDL/LDL ratio [8]. Moreover, an investigation on 420 Japanese population showed a positive association between DNA methylation of LINE-1 gene and LDL/HDL ratio and weakly and negatively association with HDL [13].
LINE-1 gene is retro-transposons that have remained active in the human genome. LINE-1 composes 17% of DNA in human [32]. Retro-transposons are a type of genetic component that can copy and paste themselves into different genomic locations. Therefore, they could be disruptive for nearby genes or regulatory sequences [33]. Epidemiological studies showed LINE-1 methylation was associated with metabolic syndrome and cardiovascular disease [8,21]. A case-control study on 108 Spanish participants showed no significant association between methylation in six CpG sites of LINE-1 and HDL and LDL levels [9].
Differences in the quantified LINE-1 DNA methylation sites lead to difference in methylation levels [13]. Some studies showed that severe obesity (BMI ≥ 40 kg/m 2 ), age and antihyperlipidemic drugs were associated with alterations in LINE-1 DNA methylation and dyslipidemia [13,29,34,35]. Age may be negatively associated with LINE-1 DNA methylation levels [36]. Findings showed that inflammation markers including C-reactive protein (CRP) and interleukin-6 (IL-6) were associated positively with DNA methylation in leukocytes. IL-6 regulates the methyltransferase gene and might lead to epigenetic changes. Obesity and inflammation may fluctuate global DNA hyper-methylation [37,38].
Some studies showed that women had significantly lower levels of LINE-1 methylation [10,39,40]. Different levels of hormonal factors and dietary folate or other one-carbon nutrients in men and women might lead to these differences between genders [41][42][43]. However, the reason of difference between genders has not been determined exactly and some studies claimed that male/ female hormone differences were not the cause of these differences [43,44].
Physical activity is another factor that is associated with DNA methylation. Higher physical activity levels are associated with higher LINE-1 methylation [45,46]. Study on subjects with glucose metabolism disorder showed that physical activity intervention improved impaired glucose metabolism and decreased LINE-1 methylation in blood cells [47].
Some studies showed that smoking status can be correlated with DNA methylation [10,40]. However, another study did not confirm this finding [48]. About the relationship between age and DNA methylation, several studies did not showed any association between LINE-1 methylation levels and age [43,48].
ABCG1 is another gene sequence in our study that has a critical role in lipid homeostasis. In macrophage, ABCG1 involves in phospholipid transport and improves the efflux of cellular cholesterol to HDL. Also, it has lipid regulating function in other cells like pancreatic beta cells [49]. Due to its role in lipid regulation, ABCG1 affects lipid levels, obesity and diabetes [50]. Ligand-activated retinoic acid receptor and peroxisome proliferator activated receptor α/γ increase ABCA1 and ABCG1 expression [51,52]. Findings of a large population-based cohort showed ABCG1 methylation at cg06500161 had a reverse association with HDL and triglyceride levels. The expression of ABCG1 may mediate these association [11]. ABCG1 expression might influence on the association between cg06500161 methylation and lipid profile levels [11]. However, there is not any findings that showed a direct relationship between ABCG1 and triglyceride levels. ABCG1 expression is correlated with genetic variants in the ABCG1 promoter and can influence on lipoprotein lipase bioavailability [53].
Methylation-dependent transcription factor binding mediates the reverse relationship between ABCG1 methylation (cg06500161, cg27243685) and ABCG1 mRNA levels. There is opposite association between HDL-C and triglyceride levels and ABCG1 mRNA levels [54].
LEP encodes leptin, a protein that plays an essential role in regulating appetite, energy homeostasis, and obesity. A prospective birth cohort study showed LEP methylation were related to maternal metabolic status and fetal growth in pregnancy. Also, LEP methylation was associated with infancy and childhood obesity [55]. Moreover, leptin influences on immune system, inflammation, hematopoiesis, angiogenesis, reproduction and bone formation [56,57]. A study on DNA sample of blood, subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) showed that DNA methylation levels at LEP-CpG11 and CpG17 in blood and SAT were positively associated with fasting LDL levels [29]. These two CpGs involved in regulation of LEP gene [58,59]. Findings showed that responsiveness to a low-calorie diet could be correlated with both TNF and LEP DNA methylation [60].
ADRB3 encodes a protein of beta-adrenergic receptors family. This protein improves lipolysis in adipose tissue and thermogenesis in skeletal muscle. Furthermore, ADRB3 mediates the catecholamine-induced activation of adenylate cyclase and has anti-diabetes and anti-obesity effects [61]. An investigation on 61 familial hypercholesterolemia patients showed higher ADRB3 DNA methylation levels were significantly associated with LDL levels. After adjustment with age, blood lipid profile and ADRB3 gene promoter genotype, ADRB3 DNA methylation levels in obese men were lower than familial hypercholesterolemia men [28]. DNA hypermethylation of gene promoter was correlated with reduction of gene expression. However, there was positive association when DNA methylation influenced on the binding of potential transcription repressors [62][63][64].

DNA methylation and blood glucose and HbA1C
The findings of the present meta-analysis showed a positive association between ABCG1 methylation and HbA1C. There was no significant association between DNA methylation of LINE1, ABCG1 and SREBF1 genes and glucose levels. A study on Indian-Asian populations reported that DNA methylation of ABCG1, SREBF1 and PHOSPHO1genes were meaningfully associated with HbA1C and glucose levels [16]. Also, an investigation on 228 individuals, aged 49-51 years, from the Newcastle Thousand Families Study (NTFS) showed significant association between LINE-1 methylation and serum glucose levels [8]. Furthermore, a prospective study in Finland on non-diabetic population showed DNA methylation of SREBF1 and ABCG1 genes were associated with HbA1C, glucose levels and type II diabetes risk [12]. However, research on a population undergoing a biliopancreatic diversion with sleeve gastrectomy to treat obesity showed LINE-1 methylation was negatively associated with fasting glucose levels [7].
A population-based study, on 1448 non-diabetic individuals from the region of Augsburg showed association between ABCG1 methylation at cg06500161 and fasting glucose, 2-hour glucose and fasting insulin. In addition, DNA methylation at cg06500161 was oppositely correlated with its expression [25].
PHOSPHO1 that encodes the bone-specific phosphatase involves in energy metabolism disorders. However, the exact mechanism remains unclear [65]. Moreover, due to its role in arterial wall mineralization, PHOSPHO1, can be considered as a therapeutic target for cardiovascular disorders, obesity and diabetes [66]. An animal study on mice reported that PHOS-PHO1 inactivation improved glucose homeostasis, including glucose tolerance and insulin sensitivity [65]. However, there are limited studies about PHOSPHO1 methylation and glycemic index, especially insulininduced indexes.
SREBF1 gene encodes transcription factors that is correlated with energy homeostasis. This factor promotes glycolysis, lipogenesis, and adipogenesis. SREBP1 is a good candidate gene for obesity and obesity-related metabolic disorders like type II diabetes and dyslipidemia because it is an intracellular cholesterol regulator that is located on the endoplasmic reticulum [67].

DNA methylation and blood pressure
Our study showed DNA methylation of ABCG1 and LINE1 genes were associated with blood pressure. One study on Indian-Asian population showed positive association between ABCG1 methylation and systolic and diastolic blood pressure [16]. DNA methylation at cg06500161 is associated negatively with ABCG1 expression in blood [11,16]. A study on 1328 European population showed LINE-1 methylation was inversely associated with diastolic blood pressure. But, this association on systolic blood pressure was weaker than diastolic blood pressure [22]. DNA methylation regulates several biological pathways that are involved in hypertension pathogenesis. The renin-angiotensinaldosterone system (RAAS) is the best known biologic pathway; DNA methylation on related genes is strongly associated with hypertension incidence [68]. However, focus only on single gene methylation or single regulatory pathways and identify specific mechanism related to hypertension progression are difficult [69]. Moreover, other factors including ageing, obesity, smoking, nutrition, sex and etc. affect hypertension that should be considered [70].
The limitation of the present study is selection of only English language articles. It may lead to publication bias and an overrepresentation of effective interventions. The advantages of the present study are assessment of methylation of sex different genes including LINE1, ABCG1, SREBF1, PHOSPHO1, ADRB3 and LEP and different cardiometabolic risk factors including HDL, LDL, HbA1C, blood glucose and blood pressure.

Conclusion
DNA methylation can influence on cardiometabolic risk factors. Alteration of DNA methylation at LINE-1, ABCG1, and LEP sequences affected LDL levels. ABCG1 and LINE1 methylation influenced on blood pressure. Moreover, ABCG1 methylation was significantly associated with HbA1C as a preventive factor for glycemic status. So, DNA methylation modification should be considered to develop a new methods for prevention, treatment and follow up of cardio-metabolic risk factors. Further studies can be designed on another factors such as drugs and nutrients that can control DNA methylation.